Interactive Multi-objective Dynamic Optimization of Bioreactors under Parametric Uncertainty

被引：15

作者：

Nimmegeers, Philippe ^{[1
,2
,3
]}

Vallerio, Mattia ^{[1
,2
,3
]}

Telen, Dries ^{[1
,2
,4
]}

Van Impe, Jan ^{[1
,2
]}

Logist, Filip ^{[1
,2
,3
]}

机构：

[1] Katholieke Univ Leuven, Dept Chem Engn Chem & Biochem Proc Technol & Cont, Gebroeders Smetstr 1, B-9000 Ghent, Belgium

[2] Katholieke Univ Leuven, OPTEC, Optimizat Engn Ctr Of Excellence, Kasteelpk Arenberg 1, B-3001 Leuven Heverlee, Belgium

[3] BASF Antwerpen NV, Scheldelaan 600, B-2040 Antwerp, Belgium

[4] Ernst&Young, De Kleetlaan 2, B-1831 Machelen, Belgium

来源：

CHEMIE INGENIEUR TECHNIK | 2019年 / 91卷 / 03期

关键词：

Multi-objective optimization; Robustness; Sigma point method; Uncertainty propagation; NONDOMINATED SORTING APPROACH; NORMAL-BOUNDARY INTERSECTION; MULTICRITERIA OPTIMIZATION; DECISION-SUPPORT; ROBUST OPTIMIZATION; ALGORITHM; DESIGN; IMPLEMENTATION;

D O I：

10.1002/cite.201800082

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

Model-based optimization techniques play a key role in achieving a sustainable operation of biochemical processes. Models are an approximation of the real process under study, hence, uncertainty is inherently present and for a sustainable process operation this uncertainty should be accounted for. In practice, optimality with respect to different conflicting objectives is required and multi-objective optimization is a valuable tool. In this article the sigma point approach is applied to account for parametric uncertainty in the frame of interactive multi-objective bioprocess optimization.

引用

页码：349 / 362

页数：14

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